DocumentCode :
2823850
Title :
Enhanced maximum likelihood location estimation in wireless sensor networks
Author :
Shao-I Chu ; Kun-Ta Hsieh ; Yan-Haw Chen
Author_Institution :
Dept. of Inf. Eng., I-Shou Univ., Kaohsiung, Taiwan
fYear :
2010
fDate :
15-17 Nov. 2010
Firstpage :
239
Lastpage :
242
Abstract :
This paper develops the enhanced maximum likelihood (ML) estimation approaches for localization over the wireless senor networks. These new ML-based schemes innovatively take into consideration the probability distribution of the received signal strength of the detectable anchor nodes. Simulation results demonstrate that the proposed approaches significantly improve the estimation accuracy as compared to the existing localization methods. Moreover, these new schemes are generic and suitable for the random deployment of the wireless sensor nodes.
Keywords :
maximum likelihood estimation; wireless sensor networks; detectable anchor nodes; maximum likelihood location estimation; probability distribution; received signal strength; wireless sensor networks; localization; maximum likelihood estimation; received signal strength indicator (RSSI); wireless sensor network;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Wireless Sensor Network, 2010. IET-WSN. IET International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1049/cp.2010.1060
Filename :
5741102
Link To Document :
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